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Record W4409036851 · doi:10.1016/j.ajpc.2025.100978

Recognition and management of persistent chylomicronemia: A joint expert clinical consensus by the National Lipid Association and the American Society for Preventive Cardiology

2025· article· en· W4409036851 on OpenAlexaff
Seyedmohammad Saadatagah, Miriam Larouche, Mohammadreza Naderian, Vijay Nambi, Diane Brisson, Iftikhar J. Kullo, P. Barton Duell, Erin D. Michos, Michael D. Shapiro, Gerald F. Watts, Daniel Gaudet, Christie M. Ballantyne

Bibliographic record

VenueAmerican Journal of Preventive Cardiology · 2025
Typearticle
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsUniversité de MontréalUniversité du Québec à Chicoutimi
FundersNational Heart, Lung, and Blood InstituteNational Institutes of HealthJohns Hopkins UniversityAmerican Heart Association
KeywordsMedicineInternal medicineFamily medicine

Abstract

fetched live from OpenAlex

• Chylomicronemia is currently categorized only as familial (FCS) or multifactorial (MCS). • Chylomicronemia can be categorized by TG course as intermittent or persistent (PC). • Most chylomicronemia cases can be managed with lifestyle changes and conventional drugs. • Patients with PC and alarm features have a very high risk of acute pancreatitis, similar to FCS. • Patients with PC and very high risk may need novel therapies like apoC-III inhibitors. Extreme hypertriglyceridemia, defined as triglyceride (TG) levels ≥1000 mg/dL, is almost always indicative of chylomicronemia. The current diagnostic approach categorizes individuals with chylomicronemia into familial chylomicronemia syndrome (FCS; prevalence 1–10 per million), caused by the biallelic combination of pathogenic variants that impair the lipolytic action of lipoprotein lipase (LPL), or multifactorial chylomicronemia syndrome (MCS, 1 in 500). A pragmatic framework should emphasize the severity of the phenotype and the risk of complications. Therefore, we endorse the term “persistent chylomicronemia” defined as TG ≥1000 mg/dL in more than half of the measurements to encompass patients with the highest risk for pancreatitis, regardless of their genetic predisposition. We suggest classification of PC into four subtypes: 1) genetic FCS, 2) clinical FCS, 3) PC with “alarm” features, and 4) PC without alarm features. Although patients with FCS most likely have PC, the vast majority with PC do not have genetic FCS. Proposed alarm features are: (a) history of recurrent TG-induced acute pancreatitis, (b) recurrent hospitalizations for severe abdominal pain without another identified cause, (c) childhood pancreatitis, (d) family history of TG-induced pancreatitis, and/or (e) post-heparin LPL activity <20 % of normal value. Alarm features constitute the strongest risk factors for future acute pancreatitis risk. Patients with PC and alarm features have very high risk of pancreatitis, comparable to that in patients with FCS. Effective, innovative treatments for PC, like apoC-III inhibitors, have been developed. Combined with lifestyle modifications, these agents markedly lower TG levels and risk of pancreatitis in the very-high-risk groups, irrespective of the monogenic etiology. Pragmatic definitions, education, and focus on patients with PC specifically those with alarm features could help mitigate the risk of acute pancreatitis and other complications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.023
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0050.002
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0070.004
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0030.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.329
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2025
Admission routes1
Has abstractyes

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